AI Generated a Technical Report, and the Engineer Had to Redo the Entire Thing

Artificial intelligence can produce a technical report in just a few minutes. The problem begins when the document looks correct but contains information that does not reflect the actual project conditions.

In a discussion among civil engineering professionals, several cases were reported in which AI-generated documents had to be redone because they contained incorrect information. Another account described an impact assessment that combined European and North American standards without properly establishing which requirements applied.

These cases highlight a risk that deserves attention: well-written text can convey a level of confidence that its content does not justify. And in engineering, an error in a document can extend beyond the page and affect field execution.

The Problem Is Not Just the Error, but How Correct It Appears

A technical report may have a well-organized structure, appropriate language, and seemingly consistent conclusions, yet still be based on an incorrect assumption, cite an unsuitable reference, or overlook a project-specific condition.

The difficulty is that these errors are not always obvious on the first read. Unlike information that is clearly absurd, a plausible answer can go unnoticed, especially when the person reviewing the document does not verify the source of each criterion used.

This is where AI requires careful handling. The tool can help organize information, summarize documents, and prepare an initial draft of a report. But a polished presentation does not prove that the content is technically sound.

In Engineering, Context Changes the Answer

A standard cannot be selected simply because it appears relevant to the subject. Its applicability, the edition being used, the contractual requirements, and the specific project conditions must all be checked.

The same applies to calculations, specifications, and construction procedures. An answer may seem generally appropriate and still fail to meet the requirements of a particular project, piece of equipment, or stage of construction.

Therefore, when AI is used to prepare or review technical documents, checking whether the text is well written is not enough. The sources, assumptions, criteria, and consistency of the conclusions with the actual project information must also be verified.

If any of these steps is skipped, the tool may speed up document production without ensuring technical accuracy.

The Greatest Risk Emerges When the Document Becomes Part of Daily Construction Operations

An error in a report does not necessarily remain confined to the documentation. Depending on the content and how it is used, incorrect information can influence a specification, an inspection, an engineering decision, or the authorization to proceed with an activity.

Consider a procedure prepared using a reference that does not apply to the situation being assessed. If that information is incorporated into the project documentation and used without proper verification, the crew may follow an unsuitable criterion without realizing where the problem originated.

That is the most critical point: an AI-generated error can become part of routine operations as if the information had already been verified. Once that happens, identifying the source of the failure becomes more difficult, particularly when there is no traceability of the sources consulted and the reviews performed.

The time saved when preparing the document may ultimately be spent checking and correcting it or, in more serious situations, reviewing decisions made on the basis of that information.

Technical Review Must Go Beyond Reading the Document

Using AI in engineering does not necessarily mean compromising quality or professional responsibility. The risk lies in treating a generated response as though it had already undergone a technical review.

Before incorporating AI-generated content into an official document, several points need to be checked:

• Sources: Do the cited references exist, and do they support the information presented?

• Technical criteria: Are the standards, specifications, and assumptions applicable to the situation being assessed?

• Project context: Does the response account for actual jobsite conditions and current project documents?

• Traceability: Can the origin of the information and the checks performed be identified?

• Approval: Has the responsible professional reviewed the content before using or approving it?

  
  

These checks are not an additional formality. They are what distinguishes material produced with AI assistance from a technically validated document.

The Tool Can Help, but Responsibility Does Not Disappear

Artificial intelligence has a place in engineering, particularly in activities involving information organization, document analysis, and decision-making support. However, its use must account for the tool's limitations and the requirements of each task.

Reports of documents that had to be redone do not prove that AI is incapable of contributing to technical work. They show that trusting the appearance of an answer without verifying its content can introduce errors precisely where accuracy is essential.

In construction, information is only valuable when it reflects actual project conditions and can support the decision for which it is being used.

The question, therefore, is not simply whether AI can produce a report in a few minutes. It is whether the information in that report has been verified before someone uses it to make an engineering decision.